Responsible AI is moving from a buzzword to becoming a business imperative, especially as companies across the Asia-Pacific (APAC) region start to look at mitigating the growing risks posed by AI technologies they are implementing.
While responsible AI is gaining traction, experts emphasise that significant gaps remain in the practical implementation of these initiatives.
In an exclusive interview with iTNews Asia, Tej Randhawa, Responsible AI Lead, APAC at Accenture, discusses the current state of responsible AI adoption, the challenges faced by companies, and the path forward to bridging the gap between strategy and execution.
In a recent Accenture survey, nearly half of APAC's companies view responsible AI as a growth driver. However, the alarming reality is that only 1 percent are fully prepared to mitigate AI risks. While Southeast Asia is advancing in responsible AI efforts, the gap between organisational ambition and operational maturity is substantial.
“Operational maturity for responsible AI remains low across industries in Southeast Asia, despite the fact that more than three-quarters or 78 percent of companies have established responsible AI programs,” Randhawa noted. “This highlights the challenge of translating strategy into action.”
Responsible AI risks, such as bias, deepfakes, hallucinations, and privacy breaches, have increased, and these risks, coupled with demographic diversity and a strong consumer base, make it essential for organisations to address AI's broader societal impact.
How should one look at managing AI risks?
Prioritising privacy, data governance, and security, Randhawa asserts, will help mitigate these risks and ensure responsible AI scaling.
While operational maturity remains a challenge across industries, Randhawa identified certain sectors leading the charge. The banking sector stands out due to its highly regulated nature and significant prior investments in risk management and controls. Government agencies and the public sector, particularly in countries like Australia, are also advancing responsible AI adoption due to mandatory AI standards.
“Industries serving customers at scale, such as retail, telecommunications, and consumer goods, are rapidly adopting responsible AI, especially driven by hyper-personalisation and AI-driven customer engagement,” Randhawa explained. “Life sciences, particularly in R&D and clinical applications, are also witnessing accelerated AI adoption.”
As regulatory frameworks evolve, he expects responsible AI adoption to accelerate across all sectors, marking the next phase of AI maturity in the region.
Navigating challenges in Responsible AI
When asked about the challenges faced by organisations in implementing responsible AI practices, Randhawa pointed to the modernising of digital core infrastructures and data platforms as significant hurdles. Companies are also grappling with a fragmented regulatory landscape and a shortage of skilled AI professionals.
“Developed nations like Singapore, which already have established frameworks, are better positioned to overcome these barriers compared to emerging economies that face greater challenges in regulatory alignment and infrastructure readiness,” Randhawa added.
“While financial concerns and ROI measurement are important, the real roadblocks often lie in organisational readiness, regulatory frameworks, and access to AI talent,” he said.
Despite these challenges, Randhawa says responsible AI can play a role in driving business growth and innovation, adding that organisations pioneering in responsible AI can see an increase in AI-related revenue. “Responsible AI isn’t just about compliance; it’s about business success, trust, and sustainability.”
A recommended approach companies can take
For companies looking to develop responsible AI, Randhawa emphasised the importance of investing in risk management, third-party audits, employee training, and AI-specific cybersecurity. “These investments mitigate risks, build trust, and ensure compliance with evolving regulatory standards,” he said.
He also advised companies to frame responsible AI not just as a compliance requirement but as a strategic tool.
Responsible AI enhances brand reputation, ensures data privacy, strengthens compliance, and optimises operations, offering a competitive edge and new market opportunities. Companies that embrace responsible AI early on will not only comply with regulatory standards but also attract top talent and foster long-term growth.
- Tej Randhawa, Responsible AI Lead, APAC at Accenture
Randhawa said organisations in Southeast Asia are gradually recognising the long-term value of responsible AI, moving away from short-term gains toward a strategy that prioritises trust, security, and sustainability.
“This shift reflects a growing understanding that responsible AI is integral to long-term success, building a foundation of trust, compliance, and operational excellence,” he added.
Ways to overcome the gap
Despite the growing awareness, closing the gap between ambition and execution remains a challenge. According to Randhawa, human interaction risks, poor-quality training data, and difficulties embedding fairness are some of the key obstacles.
To close this gap, organisations must take proactive steps, including increasing investments in AI governance, implementing clear policies, and ensuring third-party accountability.
Randhawa advocates a holistic, cross-functional approach to AI responsibility, with clear policies, regular audits, and an emphasis on fairness and risk mitigation.
Looking ahead, Randhawa predicts that emerging technologies like federated learning, differential privacy, and explainable AI will play a pivotal role in the evolution of responsible AI.
"Explainable AI (XAI) will transition from a research concept into a practical necessity," he said, noting that companies will integrate XAI capabilities into their AI pipelines to enhance transparency and foster trust with customers and regulators.
As responsible AI practices mature, new roles such as “AI ethicists” and “explainability engineers” will emerge, highlighting the growing importance of ethical AI development.
For organisations just beginning their responsible AI journey, Randhawa recommended starting by establishing a strong data foundation, embedding responsible AI principles into operations, and fostering trust among employees and customers.
By taking these steps, companies can ensure they are on the right path toward scaling AI responsibly and creating long-term value, he added.
